South Africa’s Gauteng provincial government is using machine learning-powered technology to monitor, track and predict COVID-19 infections across the province.
The technology has been developed in a collaboration between the provincial government, IBM Research Africa, Wits University and other stakeholders in an effort to create an epidemiological model of the province’s infection trends and provide a roadmap for containment measures.
IT Web reports that the system runs on IBM’s cloud-computing infrastructure and shows snapshot views of the virus’ spread.
‘Timely and accurate data analysis can help governments stay ahead of new transmissions and flatten the curve,’ says Ashley Gritzman, research scientist at IBM Research Africa. ‘The platform is being used by the Gauteng provincial government in their war room to understand the progression of COVID-19 and then make informed decisions on how to better respond to it, using machine-learning-powered spatial monitoring, reporting and predictive analytics tools focused on various elements of the COVID-19 infection trends.’
The technology identifies hotspots and helps the authorities understand the risk factors of COVID-19 (such as high-density dwelling areas), enabling them to allocate medical resources required to handle to expected peak period where they are needed the most.
Gritzman adds that while some aspects of the platform are already in use by the Gauteng government, the long-term vision is to enable the province’s citizens to also use it to gain insights of the infection trends in their neighbourhoods.
